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Information Theory, Inference & Learning Algorithms

Pages
640
Published
2003
Language
English

Synopsis

Explore the foundational principles of information theory and its practical applications in this comprehensive textbook. Learn about communication systems, data compression, and error-correction, alongside a suite of inference techniques like Monte Carlo methods and neural networks. This resource offers a deep dive into Shannon's theory and probabilistic data modeling, complete with examples and exercises for students and researchers alike.

About the author

D
David J.C. MacKay

Professor of Natural Philosophy, Department of Physics, Cavendish Laboratory, University of Cambridge